Human-Machine Collaboration for Leadership Preparation

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Authors: M. Elizabeth Azukas, David Gibson
Cited by: 0

Abstract

This mini-ethnographic case study explores the potential of generative artificial intelligence (AI) large language models (LLM) to enhance leadership preparation outcomes. The study investigates the perceptions of aspiring principals regarding the potential of generative AI to enhance leadership preparation. Findings suggest that LLMs can enhance principal preparation courses through content creation, adaptation, and optimization. AI-mediated conversations offer opportunities to address "soft" skill gaps and apply content knowledge. The study discusses the benefits and challenges of using an LLM in educational leadership preparation and underscores the importance of effective prompt engineering. The implications for future research are considered, emphasizing further exploration of AI in educational simulations and the competencies required for effective human-machine collaboration in education.

Fields of Study & Subjects

Artificial Intelligence in Education Artificial Intelligence in Healthcare and Education Intelligent Tutoring Systems and Adaptive Learning

Publication details

Journal / source
AI-Enhanced Learning
Volume
2
Issue
1
Pages
123–145
Publication date
1 January 2026
Language
EN